HomeMy WebLinkAbout#15 IRP Plan AGENDA ITEM #15
Public Utility District m
MEETING DATE: April 3, 2024
TO: Board of Directors
FROM: Jared Carpenter, Electric Utility Director
SUBJECT: Considering the Approval of the District's Integrated Resources Plan
(IRP)
APPROVED BY:
Brian C. Wright, General Manager
RECOMMENDATION:
A. Provide feedback and direction to staff; and
B. Approve the District's Integrated Resource Plan (IRP) as proposed.
BACKGROUND:
The District commissioned Aspen Environment Group, along with subcontractors Flynn
Resource Consultants Inc. (Flynn RCI), to prepare the District's first Integrated
Resource Plan (IRP) in May 2023. The purpose of an IRP is to forecast future energy
and demand loads, and to match the energy resources needed to comply with state,
federal, and local policies and regulations.
ANALYSIS AND BODY:
Based on the District's historic annual growth of 2.1% per year, the IRP forecasts three
energy demand scenarios that capture varying degrees of energy use, customer
photovoltaic generation, electric vehicle charging, building electrification and energy
efficiency. The IRP also addresses methods to comply with the state Renewable
Portfolio Standard (RPS), Greenhouse Gas (GHG) reduction mandates, and energy
efficiency program goals all while ensuring system reliability at or above industry
standard and with an eye towards potential rate impacts to customers. To meet this
growth, the IRP recommended a Balanced Portfolio of generation that includes wind,
solar, geothermal, hydroelectric, natural gas, energy efficiency, and energy storage
options to ensure reliable, cost-effective, and regulatory-compliant sources of energy.
As IRP milestones are achieved (energy forecasts, new generation, energy efficiency,
etc.) and regulatory mandates are met (RPS, PCL, GHG), Staff will update the IRP
accordingly and report to the Board in the annual Purchase Power Review, budget, or a
special report.
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The development of the 2024 IRP is a guidance document, providing direction for
future resource decisions. it is not a procurement document. All future procurement
activities will be evaluated independently and brought to the Board fro review each
year. This report will be updated at least once every five years and submitted for the
Board's review and approval.
GOALS AND OBJECTIVES:
District Code 1 .05.020 Objectives:
1. Responsibly serve the public.
2. Provide a healthy and safe work environment for all District employees.
4. Provide reliable and high quality electric supply and distribution system to meet
current and future needs.
5. Manage the District in an environmentally sound manner.
6. Manage the District in an effective, efficient and fiscally responsible manner.
District Code 1 .05.030 Goals:
1. Manage for Financial Stability and Resiliency
2. Environmental Stewardship: Create a sustainable resilient environment for all our
communities.
3. Engage with our customers and communities in a welcoming and transparent way to
identify opportunities.
4. Take the best of private sector thinking to modernize the utility and add value to our
communities.
5. Developing an inclusive culture drives organizational integration and success.
FISCAL IMPACT:
There is no direct fiscal impact associated with this item. However, the IRP will serve
as a strategic roadmap for the District's future energy procurement strategies.
ATTACHMENTS:
1. Attachment A - 2023 Truckee Donner PUD Integrated Resource Plan
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�TRV EKE E DEN N E R
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Integrated Resource Plan
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DRAFT
December 15, 2023
Truckee Donner Public Utility District
2023 Integrated Resource Plan
Table of Contents
ExecutiveSummary.......................................................................................................................................2
Introduction and Purpose.............................................................................................................................4
LoadForecast................................................................................................................................................5
Overview...................................................................................................................................................5
Methodology on Load Modifiers and Sensitivities ...................................................................................8
Resultsand IRP Inputs.............................................................................................................................12
Resources....................................................................................................................................................13
ExistingResources...................................................................................................................................13
FutureResources....................................................................................................................................15
IRP Model Features and Key Assumptions .............................................................................................17
Load-Resource Balance Cost Primary Scenarios.........................................................................................21
Overviewof IRP Methodology................................................................................................................21
ResourcePortfolios.................................................................................................................................22
SensitivityAnalysis..................................................................................................................................30
Conclusion...................................................................................................................................................33
Appendix A: District's Compliance with Key State Policy Legislation and Goals ........................................34
Appendix B: Additional IRP Model Assumptions and Findings...................................................................36
Appendix C:Additional Load Forecast Methodology.................................................................................39
Appendix D: Exploratory Load Scenarios....................................................................................................41
AppendixE:Acronym List...........................................................................................................................42
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Truckee Donner Public Utility District
2023 Integrated Resource Plan
Executive Summary
The Truckee Donner Public Utility District (TDPUD or District) commissioned Aspen Environment
Group, along with subcontractors Flynn Resource Consultants Inc. (Flynn RCI) and Better Climate
(the Team), to prepare this first-ever Integrated Resource Plan (IRP) in May 2023. The team met
with District Staff to clarify scope and launch the project in July. The team requested data and
met with staff several times to exchange information and draft results. This report presents our
analysis and findings.
The analysis consists of two key parts: the demand forecast and the resource analysis. We
present three main and three alternative demand scenarios, with the alternatives designed to
capture additional uncertainty. The "mid" case demand forecast reaches 247 GWh and 47.5 MW
by 2040. High and low alternatives capture varying degrees of photovoltaic generation behind
the customer meter, electric vehicle charging, building electrification and energy efficiency. We
found the District's load to have grown in recent years by 2.1%; the low and high demand cases
modify that growth rate as well as assumptions for the various additional forecast elements. We
also note that the district, in all cases, remains a winter-peaking utility. An important implication
of this observation is that holding enough resources to be resource adequate in winter means
the District will have excess to sell during summer, when most of the other utilities in the region
reach their peak loads.
On the resource side, we analyze five different resource portfolios. For each, we compute a net
present value (NPV) cost as shown in Table ES-1 below and evaluate the portfolio to ensure that
it meets peak month and hourly load, meets resource adequacy requirements, has the required
renewable portfolio content and meets zero-carbon, or greenhouse gas, requirements.
Table ES-1 Scope and Cost (M$) Performance of Recommended Portfolio Relative to
Alternative Portfolios
Portfolio Name Portfolio Description NPV(M$)
Recommended Balanced Portfolio $201.5
No New PPA(NNP) No new contracted resources,and rely solely on $229 0
market purchases for incremental needs
No CVP, No Stampede,Add 4MW each of new
No CVP, No Stampede utility-scale solar&4-hour storage, 1MW of TDPUD $210.8
storage and 2MW of community solar
No Storage, High Geothermal No battery storage(4-hr or 8-hr)and 4.5MW more $192.6
geothermal resource
Increase community solar by 10 MW, Internal 4-
High Internal Gen hour battery storage by 3MW, Utility-scale 4-hour $217.6
battery storage by 2.5MW, and reduce geothermal
by 3MW.
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We assess a range of sensitivities, selected to capture the impact of key uncertainties. These
include natural gas costs, prices for power purchase agreements, the transmission charge to
transport electricity across the NV Energy system, how the resources are counted toward
resource adequacy, variability in how much hydro-electric generation occurs in a year and the
pattern of change between wet and dry years. Last, the Team tests the impact of deliveries to
the District from the Central Valley Project being exempt (or not) from low voltage transmission
access charges. The sensitivities allow one to evaluate how different resource combinations
compare in terms of not only cost, but the various key uncertainties.
In all,the Team recommends what we call the Balanced Portfolio. It is not the absolute least cost
portfolio, but its composition yields the best balance of risk and cost across the various
sensitivities. The Recommended portfolio is reliable in that it meets all projected demand and
maintains an adequate planning reserve margin. It offers lower procurement cost than others
we assembled and reduces exposure to market volatility. It complies with the State's
environmental goals and policies. It includes required resource diversity and is a good fit in terms
of balancing monthly and hourly resources against loads. We have also tested that the
Recommended portfolio performs well under a range of sensitivities. We recommend that the
District explore the potential for increasing the proportion of geothermal or other baseload
resources into the Recommended portfolio, with a corresponding decrease in reliance on solar
plus storage, since this potentially could result in lower overall costs, while also increasing
resource diversity.
If the District adopts the Balanced Portfolio, it must procure 38.5 MW of resources not currently
in its resource mix by 2030 and an additional 7.5 MW by 2035. Importantly, we include in the
portfolio a significant amount of solar plus storage. The Balanced Portfolio includes 2 MW of
Community Solar and 1 MW of battery storage that could be located locally, and additional local
solar and storage resources could be pursued, if feasible.
The District, in our opinion, benefits from its load profile that continues to peak in winter. This is
counter to load in most of the West,excepting the Pacific Northwest. This profile puts the District
in the position of being long resources when the weather makes California and the southwest
resource short. Even so, the West in general is seen as either resource inadequate or close to
inadequate. This, plus building and vehicle electrification, mean that the District is competing
with other utilities to buy resources, and greenhouse gas goals mean those resources must be
renewable. Additionally, we encourage the District to continue deployment of new energy
efficiency programs, even as it electrifies. Electrification of efficient buildings assures the District
is not working against itself as it procures resources.
This very first Integrated Resource Plan for TDPUD is an important step in considering resource
options and compiling a broad resource portfolio that serves the District well. The consulting
Team is pleased to offer our detailed analysis and findings.
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Truckee Donner Public Utility District
2023 Integrated Resource Plan
Introduction . .
The Truckee Donner Public Utility District (TDPUD or District) commissioned this first-ever
Integrated Resource Plan (IRP) in May 2023. An IRP explores the resources the District has and
will need to assemble in order to meet the load. It considers load growth and ways to meet
load, including energy efficiency, current resource contracts, and new resource opportunities.
It captures statutory requirements, District goals and community desires and characteristics in
crafting a guidebook the District Board and management can use to form the District's
electricity resource portfolio.
The District was established on August 9, 1927, as a Public Utility District under Division 7 of the
State Public Utilities Code. At the time of its establishment, the District provided electric service
only. Since 1935, the District has also provided water service within the Truckee and Donner
Lake areas, with the Electric System and the District's water system maintained and operated
separately. As of December 31, 2022, the District provided electric service to 13,016 residential
and 1,632 commercial, governmental, institutional and other customers. Although residential
customers comprise over 88% of all customers, they consume only about 55% of total energy
deliveries. The District is a winter, weekend, and holiday-peaking utility with a peak demand of
around 35MW to 38MW, with a smaller but growing summer peak in July between 23MW and
25MW. The District is the sole provider of retail electric service within its service area. The
District's mission is to provide reliable, high-quality utility and customer services while
managing resources in a safe, open, responsible, and environmentally sound manner at the
lowest practical cost.
The District is a network transmission service customer under the currently effective joint Open
Access Transmission Tariff (GATT) with Sierra Pacific Power Company (SPPC) d/b/a NV Energy
(NV Energy). Its load is located entirely within NV Energy's Balancing Authority Area (BAA) and
is not directly connected to any California BAA. The District uses NV Energy's network
transmission service to import into and transport across NV Energy's transmission grid all of the
energy that is necessary to serve the District's load. The District is a Load Serving Entity (LSE)
and does not generate electricity itself. Its sources of electrical power include resources owned
and/or operated by the Utah Association of Municipal Power Systems (UAMPS), Western Area
Power Administration (WAPA), and Truckee-Carson Irrigation District (TCID), supplemented by
market purchases. The District has entered into various agreements with these entities for
electrical power which is generated from wind, solar, landfill gas, hydroelectric projects, natural
gas, and other sources. UAMPS is also the Scheduling Coordinator (SC) for all energy resources
received by the District.
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The District is unique in that while located in California, it is electrically connected to Nevada
and is virtually at the crest of the Sierra Nevada along the major Interstate and rail corridor
connecting northern California with points east and to Lake Tahoe. It is host to many second
homes, meaning that a portion of its population is seasonal. Snow load and tree shade prevent
many homes from installing rooftop solar, and the District's load currently peaks during winter
months.
The analytical team that prepared this IRP consists of Aspen Environmental Group (Aspen),
Flynn Resource Consultants Inc. (Flynn RCI), and Better Climate. The consulting team launched
its work in July 2023. This report presents our results. It is organized to first review electricity
demand, then resources, and the balance of those resources versus demand. It addresses
several key questions, including: does the District have enough electricity under contract to
meet its projected demand? How much more electricity will the District need to meet that
demand over the seventeen-year forecast period? The IRP evaluates this balance for multiple
resource mix scenarios or portfolios, calculating the net present value of total cost to the
District to meet its load and how that present value varies as the value of key input variables
vary. This allows the District to further explore resource scenarios that may have similar costs,
but a wider variance around that cost. A wider variance generally means higher risk, and may
indicate more uncertainty about the values of key inputs. the District must decide which
resource risks it is willing to take and how to manage unavoidable risks that may be associated
with different resource portfolio options. The results also calculate metrics such as whether
the identified portfolio meets the District's Greenhouse Gas emissions goals and resource
adequacy requirements that may be imposed by the State of California.
IRPs require the use of analytical tools capable of evaluating and comparing the costs and
benefits of a comprehensive set of alternative supply and demand resources. Supply options
typically include the evaluation of new conventional generation resources, renewable energy
technologies, and distributed energy resources. Demand options typically include consideration
of demand response programs, energy efficiency programs, and other "behind the meter"
options which may reduce the overall load that the utility must be prepared to supply. An IRP is
intended to launch conversation and reflection. The conversation focuses on the magnitude
and shape of the electricity load that the District must plan to meet and what resources it will
use to meet those demands. Load, its shape, the type, and cost of resources to meet it, are all
uncertain. A large part of the IRP process is to recognize that uncertainty and collectively
evaluate those uncertainties relative to the risk preferences of the District and its customers.
Overall, it is a conversation about the District's future. Aspen, Flynn RCI and Better Climate are
privileged to help lead the District's first-ever formal conversation to plan its future in this way.
Load Forecast
Overview
Aspen developed a 17-year load forecast for the District's 2024 Integrated Resource Plan. The
approach results in annual, monthly and hourly forecasts under three main scenarios and three
additional alternatives that test other potential outcomes.
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Using annual load and meter count data for the last 10 years,Aspen observes the District's annual
load grew at an average of 2.1%. Generally, this is the result of new customer hook-ups, as
demonstrated in the meter count data. Aspen assumed this 2.1% growth in the mid demand
case. We derived the low and high demand scenarios by adding and subtracting one standard
deviation from the mean growth rate. This yields 1.6% and 2.6% respectively.
Aspen modified the baseline demand for key impacts such as energy efficiency,customer-owned
photovoltaic generation, electric vehicle charging and the substitution of electricity to serve uses
supplied today by other fuels, such as natural gas. The demand impacts from these "modifying
activities" are more uncertain than the general demand trend. Aspen aggregated these by
customer class to produce the retail sales and total gross load forecast for input into the IRP. 1
Broadly, Aspen applied a time series approach to recorded consumption measured at customer
meters to derive the monthly and hourly demand patterns.2 Aspen implemented its time series
model using machine learning, operating on a python platform, using three years of automated
meter data or advanced metering infrastructure (AMI) data for each customer class, in addition
to total hourly deliveries from UAMPS to the District, back to January 2018.3
Peak demand for the District historically occurs in December and varies by 2-3 MWs each year.
Since 2014, peak demand has decreased; reaching 38 MWs in 2015 and only 34.5 MWs in January
of 2023. By 2040, we project the peak load requirement to increase to 47.5 MWs, driven by the
addition of charging load, electrification, and District population growth.
Figure 1 displays the baseline load forecast. It represents annual demand, reflecting TDPUD's
historical load, before the additional load modifiers are included.
1 The UAMPS data is"gross,"meaning that it is before accounting for transmission losses.
2 A time series is a series of data points organized in time order, earliest to latest.
s Aspen used a forecasting tool that applies decision-tree logic to increase predictive ability,correcting the errors
of the previous trees iteratively to yield a more accurate prediction. Aspen's implementation includes per capita
income, month, hour,day of year,year, holidays,day of week,and quarter as predictive variables to yield hourly
load.
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Figure 1: Baseline Annual Load Forecast (Before Load Modifiers)
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The hourly load modifiers are forecast separately and added to the baseline forecast to arrive at
the annual and monthly forecast. Figure 2 provides the resulting Mid, Low and High demand
cases which include the load modifiers and adjusted annual trend.'
Figure 2:Annual Load Forecast Scenarios
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Figure 3 shows the monthly load modifier requirement (or savings) for the mid case. Electric
vehicle charging and solar generation are highly dependent on the time of year due to weather,
seasonal residents and tourism.5
4 The nomenclature follows the CEC's demand forecast where they create a "baseline"forecast before adding
additional load modifiers and a "managed"forecast including the load modifiers for their Low, Mid,and High
demand cases.
5 Monthly load shapes are derived from TDPUD's hourly AMI data for public charging load and solar generation or
received kWh. Generated a monthly profile based off weighted meter data.
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Figure 3: Monthly Load Modifier kWh requirement(or savings)for the Mid Case
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The resulting load forecast produces monthly and peak demand.' Aspen also produced peak
hourly profiles for August and December in 2025, 2030, 2035, and 2040. These allow the
resource model to assess how various resource portfolios perform on an hourly basis as shown
later in Figure 12.
Methodology on Load Modifiers and Sensitivities
Each of the load modifiers are forecast independently using TDPUD supplied data sources and
publicly available data. Aspen focused on primary load concerns for the District including PV
adoption, electric vehicle charging, Energy Efficiency (EE), and electrifying appliances and
buildings. Where data is available, the load modifiers were forecast on an hourly basis. This
results in a load profile that identifies the District's hourly resource requirement.
Residential and commercial PV data is sourced from TDPUD's hourly AMI data and used to
develop the generation profile for solar in the Truckee area historically. This accounts for
seasonality and magnitude of solar generation by hour. PV in the commercial sector is assumed
to grow at half the rate of residential. In the base case, residential PV increases at 2.5% per year
and commercial grows at 1.25%. The higher growth is attributed to the California required
building code standards on new construction, however, growth is still considered low due to
Truckee PV exemptions, which are allowed for shade cover and heavy snow load buildings.' In
the low load case residential and commercial PV growth rates are 5% and 2.5%.
Electric vehicle charging has a large potential for load growth for Truckee as more and more EVs
are purchased coupled with the District's higher demand from more temporary residents and
s This forecast is an input into the IRP model,which assesses the resources needed to meet the load requirement.
The Twon of Truckee takes permit applications for solar PV installations. There have been limited applications to
date,and the Town of Truckee has updated guidelines for exemptions.See:
https://www.townoftruckee.com/government/community-development/building-and-safety/residential/proiect-
scope/solar
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visitors (leading to more vehicle trips) during tourist seasons.$ For residential charging, Aspen
utilized DMV data and projected Plug-in Electric Vehicle (PEV) stock using a learning curve for
new technologies.' This was then paired with an hourly charging pattern for light duty electric
vehicles from NREL to generate the load forecast. PEV market share is adjusted to fit the low and
high demand sensitivity cases. Today, PEVs represent about 3% of the vehicle stock included in
the DMV data for Truckee, increasing to 13% in the Mid case by the end of the forecast period.10
For public vehicle charging, Aspen was able to utilize TDPUD's public charging station data in
order to produce the seasonal and hourly load shape from charging. This was then coupled with
the ICF Tahoe-Truckee PEV Readiness Plan trip projections to forecast charging demand.11 The
Truckee data emphasized the impact from tourism and electric vehicle charging in the summer
and more specifically in July. The current availability of 4WD EV models is limited and results in
limited growth in public charging from PEV trips in the winter due to snow conditions.12 As more
EV models reach the commercial market the EV charging load is expected to increase in the
winter months as wel1.13
In addition to the three primary load scenarios Aspen also crafted two exploratory cases for
electric vehicle charging to test the bounds of potential charging requirements. The first
exploratory case examined the potential for heavy duty truck charging from freight moving
through the 1-80 corridor and the potential for en route charging specifically in Truckee. This
would require installation of ultra-fast DC MW charging capabilities and space for trucks to stop
and charge along 1-80. Assuming truck stop space is available, Aspen estimated an increase in
the peak load requirement of 4-6 MW.14 This case is still speculative as these trucks are not
commercially available and the charging and duty cycles have not been tested. There are also no
truck stops currently located within the District where fast charging stations could be added. The
s For the forecast we consider Plug-in Electric Vehicles or PEVs as the DMV data and ICF Tahoe-Truckee PEV
Readiness Plan both include plug-in hybrids and battery electric vehicles in their stock and trip data.
9 This uses a Bass Diffusion Curve and fit using expected market share from ICF's Tahoe-Truckee PEV Readiness
Plan. ICF's report included market share for mid, low and high case.
11 DMV data is provided by zip code,and Aspen aggregated the relevant zip codes for Truckee to come up with
historical PEV stock.
11 See page 20 for trip projections: https://www.energy.ca.gov/sites/default/files/2021-05/CEC-600-2021-030.pdf
1z The ICF Tahoe-Truckee PEV Readiness report cites the consumer preference for SUVs in Tahoe in order to
navigate snowy roads. See page 35: https://www.energy.ca.gov/sites/default/files/2021-05/CEC-600-2021-
030.pdf
13 While new EVs with AWD and 4WD will become available,there are still some limitations and downsides to
battery efficiency at low temperatures that could limit use. See:
https://pubs.acs.org/doi/epdf/10.1021/es5O5621s
14 Aspen looked at potential volume of trucks moving through the Truckee corridor however,the volume of truck
traffic likely exceeds the capacity and space requirement to charge these trucks. Charging one of these tractor-
trailers takes 1-2 hours and uses approximately 1 MW each hour. This scenario assumes 4-6 MW worth of
chargers operating at the same time. This would accommodate 50 to 100 trucks per day. See article on Charging
Specs: https://www.ptolemus.com/insight/is-testa-semi-a-game-changer-part-l-testa-semi-versus-other-electric-
trucks
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second exploratory case reviewed a bookend case where all residential vehicles are electric.15 In
this case the total load requirement increased by 26 GWh by 2040. That is about 15%of Truckee's
total demand in 2023.16
Aspen crafted a case that preserves Energy Efficiency (EE), consistent with the precepts of
Integrated Resource planning. This corresponds to EE having long been known as the cheapest
kWh of energy. For every kWh saved, that is one less kWh to be procured. The District spent an
average of $670,000 on energy efficiency programs from 2011 to 2022. Yet reported savings
declined. This means that the per unit cost of the District's EE is increasing. This is mainly
attributable to the maturity of lighting replacement programs.
Figure 4:Truckee Reported Net Annual Energy Efficiency Savings
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Figure 4 illustrates Truckee's reported net annual energy efficiency savings, sourced from CMUA
SB 1037 Annual Status Reports.17 While traditional program spending primarily targeted EE to
reduce load requirements, the same funding source is now also being allocated to electrification
incentives, contributing to increased utility load and increased resource procurement to meet
that load.
Whether the District cannot obtain cost-effective load savings from additional EE spending is
unclear. The most recent EE potential and goals study (prepared in 2020 by GDS Associates for
CMUA and submitted to the California Energy Commission) estimates the total cumulative EE
potential as 2.1% of retail sales by 2040. This suggests that the TDPUD EE programs are not yet
" PG&E states that compared to a mixed fuel home with two ICE vehicles,an all-electric home with two EVs
doubles electricity consumption for the home.See: https://www.energy.ca.gov/data-reports/reports/integrated-
energy-pol icy-report/2023-i ntegrated-energy-pol icy-report/2023-0
16 This case assumes a market share of 18,000 EVs in Truckee and utilizes the same NREL load profile for charging.
17 The CEC uses the IOU and POU reported program savings in order to produce the statewide demand forecast for
California. See CMUA's annual reports here: https://www.cmua.org/sbl037-reports
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saturated and that cost-effective EE opportunities remain more available to Truckee than to
other publicly-owned utilities.18 Whether they are or are not, the district will need to align
electrification with EE, assuring Efficient Electrification. This means that the replacement of gas
appliances and heat pump installations for residents should prioritize the use of the most
efficient appliances and that those appliances be installed in homes with efficient building
envelopes. This is essential to minimizing infrastructure upgrades and additional resource
procurement costs.
The 2023 TDPUD IRP offers three load forecast scenarios. Low load represents high EE savings
targets with baseline electrification, while the high load scenario prioritizes accelerated
electrification with EE savings limited to its recent historical (lower) value.
Figure 5: Energy Efficiency and Electrification Scenarios
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High Load Cake EE Efficient Elect r ificat ic n Case EE
High Load Case Elect=f cat on Efficient Electrificaticn Case Electrificat c-
�NET High Load Case -het Efficient Electrifieaticn
In the low load case, cumulative energy efficiency savings exceed 3 GWh by 2040, resulting from
new EE programs capturing some portion of remaining potential savings for the District.
Although EE cost ($/kWh) is assumed to increase over time due to diminishing returns from older
EE programs, in the low load scenario the cost per kWh saved declines in 2025, 2030, 2035, and
2040 as new savings programs are initiated. Electrification load growth in the low load case is
1.5 GWh by 2040 and the resulting net load is -1.6 GWh by 2040.
18 How the study reached a nearly opposite conclusion for the District versus other utilities covered in it is unclear.
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The mid case assumes historical EE savings and increasing cost($/kWh) as the programs continue
to mature and the previously "low hanging" EE savings diminish. In this scenario the growth in
load from electrification is not offset by the higher EE savings as seen in the previous case.
Electrification load reaches —1.5 GWh by 2040 as before, but cumulative EE savings are only—0.6
GWh by 2040.
The high load case demonstrates accelerated electrification of up to —3.5 GWh by 2040 and
limited EE savings. This case highlights how electrification can drive load growth and peak load
requirements when it is not coupled with EE. Similarly, EE costs are assumed to increase with
diminishing returns without new EE programs and new efficient electric appliance programs.
An additional case the District should consider is an Efficient Electrification Scenario. It
demonstrates an efficient electrification scenario modeled after the CEC's Building
Decarbonization Assessment.19 This case maximizes greenhouse gas (GHG) emissons reduction
while mitigating load growth in place of excess procurement by pairing accelerated electrification
from the high load case with the potential EE savings in the low load case. The resulting net load
under this case is 227 GWh in 2040 compared to 247 GWh in the Mid load case.
Investing in traditional EE programs, such as lighting, will almost certainly yield low savings at
higher costs. This does not mean that the District should abandon EE. The load forecast
emphasizes the importance of planning for efficient electrification to manage load growth while
aligning with California and Truckee's carbon goals. The upshot is that the District should set new
EE goals for targeted EE load reduction and add separate spending to support electrification so
that electrification is efficient.20
Forecast Results and IRP Inputs
Figure 6 provides the resulting load forecast scenarios. Total annual load varies by 21-23 GWh
between the low and high load scenarios, with a variation in the associated peak load
requirement of about 4 MW. In the high load scenario, the District reaches a peak of 52 MW in
December 2040. We understand that that the current transmission import capability of TDPUD
is limited to 52MW. Therefore, meeting a peak load beyond 52MW could require the TDPUD
could require transmission upgrades or increased reliance on local generation and/or storage as
described in the Resources section.
19 The CEC Building Decarbonization Assessment reports moving from aggressive electrification to efficient
electrification will cost 5%more in total net cost, but decreases incremental grid demand by 17%or 8,000 GWh.
20 Further detail on spending estimates and EE and electrification cost assumptions are included in the appendix.
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Figure 6: Load Forecast Scenarios
Scenario CAGR Loadin211346 PeakLoadin2d40 Description
*Historical EEtrend
,*Mid case solar
•Mid caseforresidential and public
Mid 2.22% 247G1':'7 47,5 '•r1'�;'•;'
EV charging
•Baseline Annual Trend {2.1%)
•Mid case for electrification
•Higher EE includes potential savings
•Higher residential PV adoption
•Lower case for residential and
Low 1.66% «n G;%-i 43.8[AV:'
public EV charging
* Lowercase Annual Trend; includes
mid ease electrification
*Historical EEtrend
*Mid case solar
High 2.79°fa 270G4'•!-i 52MW •High er case fo r re sid ential an d
publicEV charging
*Higher Case Annual Trend
*Accelerated electrification
Appendix C contains additional scenarios that explore the impacts of heavy duty truck charging,
100% residential PEV charging, and the Efficient Electrification scenario.
Existing Resources
Table 1 provides a summary of the District's existing and contracted power supply resources
with the District's approximate share of each resource's capacity in MWs. The resources
highlighted in green background are Renewable Portfolio Standard (RPS)-eligible,21 whereas
those highlighted in burgundy, such as Nebo Natural Gas, 5-Year Market purchases, and Spot
Market purchases are neither RPS-eligible nor Greenhouse Gas (GHG)-free resources. The large
hydro projects (>25MW in size), such as the Central Valley Project (CVP) and Veyo Waste Heat
Recovery marked in blue in Table 1, are considered GHG-free but are not RPS-eligible.
21 See Appendix A for the District's compliance with the State RPS goals.
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Table 1: Existing Power Supply Resources
Horse Butte Wind Phase I UAMPS 15
Pleasant Valley Wind UAMPS 0.25
Trans-Jordan Landfill Gas UAMPS 3.2 Expires in 2024
-•• Natural Gas • •
Veyo Waste Heat Recovery UAMPS 1.7
Red Mesa Solar UAMPS 6
5-Year Market Purchase I • •
Stampede Powerplant WAPA 4 Expires in 2024*
26 Foot Drop Hydro TCID 1 Expires in 2023*
Old Lahontan Hydroelectric TCID 2.7 Expires in 2023*
Central Valley Project WAPA 2 Available in 2025
Spot Market ` •
Trans-Jordan Landfill, gas, which is a base load resource that has been a key component of the
TDPUD's resource portfolio, currently serves about 16% of the District's annual energy
requirements. Its contract expires at the end of 2024, and is not expected to be renewed.
Therefore, it is assumed not to be available beginning in 2025. In contrast, the 26 Foot Drop
and Old Lahontan contracted resources that expire in 2023 and the Stampede resource
contract that expires in 2024, are assumed to be renewed through the duration of the planning
period of 2024-2040. The Central Valley Base Resource hydro project is assumed to be
available beginning in 2025.
Nebo Power Station -The Utah Associated Municipal Power Systems' (UAMPS) Nebo Power Station
(Nebo), a natural gas-fired generation facility located in the central Utah city of Payson, has a
maximum capacity of 146 MW. The District's agreement with UAMPS for a SMW share of
electricity typically supplies about 10%of the District's total annual energy needs . Nebo is taken
offline twice a year in April and October for a 3 to 4-week period to perform preventive
maintenance operations and minor repairs. In the IRP model, Nebo is assumed to be dispatched to
meet the hourly District net loads beyond the amounts served using the existing and future
potentially contracted resources.
Red Mesa Solar Project-The District has a 6 MW share of the Red Mesa Project, which equates to
about 10 percent of the District's total annual energy requirements. In September 2019, the Board
adopted Resolution 2019-20 authorizing the Red Mesa Tapaha Solar Project with UAMPS. The Red
Mesa Project is owned and operated by the Navajo Tribal Utility Authority (NTUA). In September
2022, the Board adopted Resolution 2022-17 authorizing the amended agreement for the Red Mesa
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Tapaha Solar Project with UAMPS with amended pricing. The project began commercial operations
on March 15, 2023.
5-Year Market Energy Purchase-The District has an existing 5-year market power purchase
contract with UAMPS for 3-4 MW of power during December through March that began on April 1,
2022, and ends on March 31, 2027. The existing 5-year market power purchase represents about
20% of the District's annual energy requirements.The market power purchase is shaped and
scheduled to the District's load profile, filling the energy 'gaps' in the District's purchase power
portfolio that are otherwise not supplied by other generation sources. The IRP model allows for a
similar product to be available beginning April 2027.
Spot Market Purchases/Sales -The market price for energy rises or falls, primarily as the cost of
natural gas changes. This is due to natural gas typically being the marginal fuel for electricity
generation; therefore, natural gas power plants typically establish the market-clearing price of
energy generation. As a consequence of increased natural gas prices and heavy demand for energy
during the hot summer months and cold winters, market energy prices have been ranging between
$100/MWh to $200/MWh for the months of July through September in Fiscal Year (FY) 2022 and
$200/MWh to $250/MWh for November and December in FY 2022. The District's market energy
purchases averaged $95.87 per MWh in FY 2022, compared to $64.60 per MWh in FY21, and $40.10
per MWh in FY20.
Future Resources
Table 2 provides a summary of the District's future candidate supply resources with the
approximate share of the resource's capacity expected to be available to the District, in MWs.
We have applied the same convention that we applied to Table 1 in terms of resources having
RPS and GHG-free attributes. The energy associated with battery storage charging is assumed
to be GHG-free, but the discharging energy is not RPS-eligible.
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Table 2: Future Power Supply Candidate Resources
® ,• ,
Horse Butte Wind Phase II UAMPS 11 2026
Geothermal Project X TBD 2.45 2027
4 Hour Solar Plus Storage Resource-Solar TBD 6 2027
4 Hour Solar Plus Storage Resource- TBD 3-7 2027
Storage
8 Hour Solar Plus Storage Resource-Solar TBD 4 2027
8 Hour Solar Plus Storage Resource- TBD 2 2027
Storage
Carbon Free Power Project (SMR) DAMPS 5 Not Available
Additional Geothermal Project N/A 4.5- 12.5 2035
New Lahontan Hydroelectric TCID 4 2025
Community Solar TDPUD 1 - 12 2027
4 Hour TDPUD BESS TBD 1 -4 2027
New 5-Year Market Purchase
The Horse Butte Wind Phase II and New Lahanton hydroelectric resources are assumed to have
the same characteristics and costs as the existing Horse Butte Wind and Old Lahanton
hydroelectric projects. The costs for the other candidate resources were based on publicly
available information about similar projects. The IRP Model described in the next section has
the flexibility to add additional candidate resources. For example, we understand that there is
interest in local generation beyond Community Solar, such as biomass, but the scale and scope
is unknown at this time. Therefore, the biomass resources were not considered.
One important goal of resource planning is to reduce carbon emissions from generating
electricity and consuming energy. Solar and wind resources meet this criterion but they
operate only in hours that the sun is visible or the wind is blowing. Hence, they must be
augmented by battery storage and/or resources with complementary availability. We modeled
a utility-scale 4-hour battery storage resource and a separate TDPUD internal 4-hour battery
storage resource. In addition, we modeled a longer-duration 8-hour battery storage resources.
All battery storage resources were assumed to have 85% round-trip efficiency.22
Another option considered is nuclear power resources. The nuclear option we assess is not
from the old, massively large and complex 1000-MW reactors that use large quantities of water
for cooling and create large amounts of spent fuel. Instead, the option here is for what are
known as a "small, modular reactor" (SMR). The Nuclear Regulatory Commission has approved
zz Round-trip efficiency is the percentage of electricity put into storage that is later retrieved.The higher the
round-trip efficiency,the less energy is lost in the storage process.
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a 50 MW design that is being deployed now. It uses thorium as the fuel, not plutonium. The
units, which are 76 feet tall by 15 feet in diameter, are each built in a factory and are identical,
allowing economies of scale and scope to reduce error, schedule and cost risk. The plants are
housed in a factory-looking building, with no large cooling towers, and take fractions of square
miles in terms of physical footprint.
UAMPS considered participating in the Carbon Free Power Project (CFPP), which would have
been located at the Idaho National Laboratory in Idaho Falls, and was envisioned to consist of
six modules and generate 462 MW. In November 2023, UAMPS and NuScale agreed to
terminate the CFPP.21 Therefore, although the TDPUD IRP model includes a provision for SMR
candidate resources, such as CFPP, it is not part of any resource portfolios considered in this
report.
Similar to the existing 5-year market power purchase contract that expires in March 2027, the
availability of a new contract is assumed at the beginning of December 2027.
IRP Model Features and Key Assumptions
Aspen and Flynn RCI developed a customized MS Excel spreadsheet model for the District's IRP.
The IRP covers the planning period of 2024-2040. It includes electric generation and load data
aggregated to monthly and annual levels. However, the underlying hourly calculations are also
performed to test the hourly supply-demand balance for each month. The IRP model tracks key
criteria for each resource portfolio. These criteria include the ability of the District to have
sufficient generation capacity to meet its peak load and planning reserve margin (PRM)24 to
comply with California Resource Adequacy (RA) requirements.25 Two additional criteria are the
ability of the resource portfolio to meet the State RPS and GHG-free goals, as described in detail
in Appendix A.
The Power Purchase Agreement (PPA) prices for the existing resource contracts are
confidential. Table 3 shows the assumed PPA prices for the generic candidate future resources
in the Base scenario.
"https://www.nuscalepower.com/en/news/press-releases/2023/uamps-and-nuscale-power-agree-to-terminate-
the-carbon-free-power-project
24 Assumed to be 15%for this IRP.
21 California Public Utilities Code Section 9620 requires local publicly owned utilities to meet a minimum planning
reserve margin set by the Western Electricity Coordinating Council..
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Table 3: Assumed PPA Prices (Nominal $)
Resource PPA Price
New Solar Resource $ 65.00/MWh*
New 4-hour Storage $ 20.00/kW-Yr*
New 8-hour Storage $ 23.00/kW-Yr*
New Geothermal Resource $ 85.00/MWh**
CFPP/SMR $ 90.00/MWh***
$130/MWh****
Community Solar
$24/kW-Yr****
4-Hour TDPUD Storage
*Source: Market intelligence applied to data from https://eta-
publications.lbl.gov/sites/default/files/utility scale solar 2022 edition slides.pdf
**Source: Market intelligence applied to data from https://geothermal.org/our-impact/stories/geothermal-
power-purchase-agreements-rise
***Source: https://ieefa.org/resources/eve-popping-new-cost-estimates-released-nuscale-small-modular-reactor
****Assumption
The New Lahontan PPA price is assumed to be identical to the recently negotiated Old Lahontan
resource. Also, we assumed a 10% premium for the Horse Butte Wind Phase II PPA price over
the Horse Butte Wind Phase I price.
The market price for energy rises or falls, primarily as the cost of natural gas changes. This is
due to natural gas typically being the marginal fuel for electricity generation; therefore, natural
gas power plants typically establish the market-clearing price of energy generation. We used
the UAMPs market price forecast for the NV Energy (NVE) area for the Base scenario and
developed two additional sensitivities, a Low and a High forecast for the planning period, as
shown in Figure 7 below.
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Figure 7: Base, Low and High NVE Market Price Forecast ($/MWh): 2024-2040
$140.00
$120.00
s � �
$100.00 `
a
$80.00
..................
y $60.00
c
W
t
Y $40.00
L
•••••• Low Base — — High
$20.00
S-
2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040
Year
Hydro conditions have a considerable impact on the District's hydro generation portfolio, including
Old and New Lahanton, Stampede, CVP, and 26-Foot Drop hydro units. Flynn RCI used data for
Northern CA hydro generation for the last 104 years- 1920-2023 to develop distributions of dry,
median, and wet hydro conditions. The probabilities of occurrence of these hydro conditions
were used to randomly assign them to the planning period of 2024-2040 as shown in Table 4
below.
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Table 4: Assumed Hydro Condition in Base Scenario
Hydro
Year Condition
in Base
Scenario
2024 Median
2025 Dry
2026 Median
2027 Wet
2028 Wet
2029 Median
2030 Wet
2031 Wet
2032 Dry
2033 Median
2034 Dry
2035 Dry
2036 Wet
2037 Dry
2038 Median
2039 Median
2040 Wet
2041 Median
The 2024 RA prices and Renewable Energy Credit (RE C)21 prices are assumed to be $8/kW-Mo
and $0.015/kWh, respectively, with an annual escalation rate of 2.5%. It is assumed that the
District's net short (Demand minus Supply) of RA capacity to meet the PRM and REC's to meet
the RPS goal are charged at these prices, whereas the District is paid for any surplus/net long.21
The District is a network transmission service customer under the currently effective joint Open
Access Transmission Tariff (GATT) of Sierra Pacific Power Company (SPPC) d/b/a NV Energy
(NVE). Therefore, the District load pays the NVE transmission charge for all its deliveries from
the NVE transmission system. Since the CVP resource is in the California ISO (CAISO) BAA, these
import deliveries are also charged the CAISO Wheeling Access Charge (WAC). In addition to
WAC charges, for deliveries that utilize transmission facilities below 200 kV, such as PG&E's
Summit Intertie Schedule Point. Low-voltage (LV) Transmission Access Charge (TAC) are applied
in addition to the WAC. Flynn RCI's proprietary TAC forecast for NVE (Base and High scenarios),
CAISO WAC, and PG&E LV TAC are shown in Figure 8 below.
26 RECs are units that represent the clean energy created by specific renewable sources, such as solar energy
resources and wind energy resources.One REC represents one megawatt-hour(MWh)of energy produced a by a
renewable energy source.
2'Recognizing the constraints on the ability to obtain REC revenues,when the District is net long,we assumed a
monthly$100,000 net REC sale revenue cap.
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Figure 8: Transmission Charge Forecast ($/kWh): 2024-2040
$0.040
2 $0.035
1- $0.030 IN
+n
$0.025
ao
s $0.020 ap
U
c $0.015 ".Op
(A'^ $0.01000
tA
&A
E $0.005
c
M
ti0 �A ti� ti0 b0 by ,2L �'� btx �< Flo b1 ,2`b be O
ti0 LO 1L LO ti0 LO LO LO LO LO ,LO ,LO 1 1 ,LO - li
Year
NV Energy Charge_Base ——— NV Energy Charge_High
CAISO WAC PG&E LV TAC
Load-Resource Balance CostScenarios
Overview of IRP Methodology
IRP is the process that utilities undertake to determine a long-term plan to ensure generation
resources are adequate to meet projected future peak capacity and energy needs while
achieving other District objectives, such as meeting Renewable Portfolio Standards and
Greenhouse Gas reduction goals. Resource plans must ensure reliability is maintained at or
above industry standard levels. IRPs should also forecast long-term costs with an eye towards
potential rate impacts to customers to ensure that the utility can monitor and track trends with
sufficient time to implement solutions to ensure reliable and affordable electric service. An
effective resource plan should also provide a reasonable degree of flexibility for the utility to
deal with uncertainty in technological change and future regulations.
IRPs utilize various economic analyses and methodologies to assess alternative scenarios (e.g.,
different combinations of supply and demand resources) and sensitivities to key assumptions to
arrive at an economically optimal resource plan (subject to various constraints, such as
regulatory mandates and local policies). We followed key steps in the resource planning
process that are standard to the industry, as outlined below.28
28 City of Palo Alto, 2018 Electric Integrated Resource Plan, PacifiCorp 2023 Integrated Resource Plan
Volume I, March 31, 2023.Also,see"Training on Integrated Resource Planning for
South Carolina Office of Regulatory Staff," located at https://eta-
publications.lbl.gov/sites/default/files/conducting a technical review of an irp.pdf
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1. Examine Planning Framework and Risks: Identify and assess challenges the utility faces
in the current business and regulatory environment.
2. Assess Needs: Develop forecasts of load changes (incorporating impacts of cost-
effective demand-side resources), existing contracts, contract terms, and operational
constraints to determine resource needs over the planning period.
3. Consider Resource Options: Evaluate available generation resources, including
centralized and distributed renewables and long-term market power purchases, to
identify the role each will play in meeting customer needs and regulatory and policy
goals.
4. Develop Resource Portfolios: Develop resource portfolios, and evaluate them
quantitatively and qualitatively to determine a preferred portfolio. Evaluation relies
upon RPS and GHG-free requirements, needs assessment, and planning data specified in
previous steps.
5. Perform Scenario and Risk Analysis: Perform detailed evaluations of preferred resource
portfolios through scenario and risk analysis to assess performance under a range of
potential market and regulatory conditions.
6. Identify Recommended Portfolio: Identify a "Recommended Portfolio" based on the
resource portfolio expected to reliably serve demand at a reasonable long-term cost,
while achieving regulatory compliance, accounting for inherent risks, and allowing for
flexibility to respond to future policy changes.
Resource Portfolios
The District's near-term (2025) electric supply portfolio comprises the following major types of
resources:
• Energy efficiency (EE);
• Federal hydro (Stampede and CVP);
• Other hydro (Old and New Lahanton, and 26 Foot Drop hydro);
• Long-term RPS-eligible PPAs, which include solar, wind, and waste heat resources;
• Natural gas-fired (Nebo);
• Contracted and spot market power purchases for monthly/hourly portfolio balancing.
For calendar year 2025, the projected contribution of the supply resources to the District's
overall electric supply portfolio is represented in Figure 9 below.
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Figure 9: Projected District Electric Supply Mix in CY 2025 by Resource Type
* Estimated Average Annual Unit Cost of 9.9 C/kWh
11.8%
6.1%
35.20
25.5%
11.4%
10.1%
Hydro ■ Waste Heat ■ Wind ■Solar ■ Natural Gas ■ Purchases (sales)
By applying the six (6) steps described under the IRP Methodology, we determined the
recommended resource portfolio that selects the resources as shown in Table 5 below.
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Table 5: Recommended Resource Portfolio Selection*
Resources Start Year End Year Capacity
Horse Butte Wind Phase 1 2024 N/A 15.00
Pleasant Valley Wind 2024 N/A 0.25
Trans-Jordan Landfill Gas 2024 2024 3.20
-•• . 2024 N/A 5.14
Veyo Waste Heat Recovery 2024 N/A 1.70
Red Mesa Solar 2024 N/A 6.00
Stampede Powerplant WAPA 4.0 2024 N/A 4.00
26 Foot Drop Hydro 2024 N/A 1.00
Central Valley Project WAPA 2.0 2025 2024 N/A 2.00
Old Lahontan Hydroelectric 2024 N/A 2.70
►� . ,- - 2024 2027 4.00
Horse Butte Wind Phase II 2026 N/A 11.05
Geothermal Resource 2027 N/A 2.45
4-Hour Solar Plus Storage Resource -Solar 2027 N/A 6.00
4-Hour Solar Plus Storage Resource -Storage 2027 N/A 3.00
8-Hour Solar Plus Storage Resource -Solar 2027 N/A 6.00
8-Hour Solar Plus Storage Resource -Storage 2027 N/A 3.00
Carbon Free Power Project 2099 N/A 5.00
Additional Geothermal Projects 2035 N/A 7.50
New Lahontan Hydroelectric 2025 N/A 4.00
Community Solar 2027 N/A 2.00
4-Hour TDPUD Storage 2026 N/A 1.00
New 5-Year Market Purchase 2027 N/A 4.00
*Except for Trans-Jordan Landfill Gas and the existing 5-Year Market Purchase, no other resource is assumed to
expire during the planning period.
In order to determine the resource portfolios, we applied the following screens.
1. Is it reliable in terms of maintaining planning reserve margin, given preconditions for
market participation and transmission provider requirements?
2. Does it minimize the overall cost of procurement, and manage market volatility,
enabling the District to offer competitive rates?
3. Does it comply with the State's environmental goals and policies?
4. Does it comply with the District's goals?
5. Does it include resource diversity?
6. Does the portfolio adequately balancing resources against loads on an hourly basis.
7. How does it perform under a range of sensitivities?
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We also considered the tradeoff between the remote utility-scale generation and within-district
resource development, such as Community Solar and TDPUD 4-hour storage. In Table 6, we
provide the pros and cons of local or behind-the-meter generation.
Table 6: Pros and Cons of Local or Behind-the-Meter (BTM) Generation
Pros Cons
BTM solar avoids NVE transmission charge, BTM resources are more expensive (higher
thereby reducing the overall cost of PPA price) than utility-scale generation
procurement
BTM storage reduces the peak net load, Large-scale buildout may not be feasible
thereby reducing RA needs and costs given the land and climate constraints in
STM solar reduces the net load, thereby Truckee
reducing the RPS requirement, and
associated cost
BTM resources provide local control
BTM resources meet environmental
stewardship goals
The projected supply mix under the Recommended portfolio is shown for four distinct years in
Figure 10.
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Figure 10: Projected District Electric Supply Mix in by Resource Type Under Recommended
Portfolio: CY 2025, 2030, 2035, and 2040
CY 2025 RESOURCE MIX CY 2030 RESOURCE MIX
-7.3%
3.8% 19.4%
00 F1i
r I wr
5.8%
25.5%
,4*
11.4%
10.1% 41.4%
.Hydro ■Geothermal ■Waste Heat .Wind
■Hydro ■Waste Heat ■Wind ■Solar ■Natural Gas ■Purchases(sales) ■Solar ■Storage ■Natural Gas ■Purchases(sales)
CY 2035 RESOURCE MIX CY 2040 RESOURCE MIX
-13.7% 9.9% -9.0%
3.0% I 15.5%
2.7%
33.4% 24.2%
27.0%
29.9%
36.9% 33.0%
Hydro ■Geothermal ■Waste Heat .Wind .Hydro ■Geothermal ■Waste Heat .Wind
,olar ■Storage ■Natural Gas ■Purchases(sales) ■Solar ■Storage ■Natural Gas ■Purchases(sales)
The Recommended portfolio shows increased reliance on renewable resources, such as
geothermal and solar resources, while reducing the District's reliance on natural-gas-fired
resources. The significant increase in contracted resources helps the District transition from
being a net buyer in the spot market in the early years (2025) to a net seller in the later years.
Contracting with RA-eligible resources allows the District in mostly comply with the 115% PRM
over the planning period with long-term contracted resources, as shown in Table 7 below.
Table 7: Performance of Recommended Portfolio in Meeting Reliability and State Policy
Criteria: CY 2025, 2030, 2035 and 2040
Criteria 2025 2030 2035 2040
Contracted PRM (%) 96%* 118% 129% 117%
Contracted RPS(%) 55% 99% 109% 104%
GHG Free(%) 59% 106% 111% 106%
* Requires additional short-term RA capacity purchases to meet 115%
PRM.The RPS target increases from 45%in 2025 to 60%in 2030.The GHG
Free target is 90%in 2035 and 95%in 2040.
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Table 7 also shows that the Recommended portfolio is compliant for the four distinct years in
meeting the State RPS and GHG-free requirements. Figure 11 confirms that this compliance
holds for the entire planning period. That is, the Recommended portfolio meets the State
policy goals by relying primarily on renewable resources that meet the RPS requirements (Top
Figure) and other GHG-free resources that count towards meeting the GHG-free goals (Bottom
Figure).
Figure 11:Tracking RPS and GHG-Free Levels vs. Requirements—Recommended Portfolio
Renewable Energy Supply vs. RPS Requirement 2025-2040
250,000,000 120%
200,000,000 ` ' 1 / 100%
s 150,000,000ODryWet
80%
Y 60%
100,000,000
40%
50,000,00020'�- 0%
Med Wet Wet Dry Med Dry Dry Wet Dry Med Med Wet
I
2025 1 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040
Hydro Condition/Year
Geothermal �Hydroelectric �Solar PV �Wind — —Average RPS Level RPS Requirement
Renewable Energy Supply vs.GHG-Free Requirements Requirement 2025-2040
250,000,000
120%
200,000,000 100%
do
L 150,000,000 8OD/o
3 ' 6OD% l7
100,000,000 x
40'D
50,000,000 ' 20'D
- 0%
Dry Med Wet Wet Med Wet Wet Dry Med Dry Dry Wet Dry Med Med Wet
2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040
Hydro Condition/Year
Geothermal Hydroelectric Solar PV Wind — — Average GHG-Free Level GHG-Free Requirement
Another key indicator is hourly portfolio fit, which will determine the degree to which the
portfolio is exposed to spot market prices. Figure 6 displays average hourly generation profiles
in CY 2040 for a representative day in the months of December (representative winter) and
August (representative Summer). The loads in these months are relative are relatively high and
low, respectively, in comparison to the District's average loads. Although total resource
supplies from long-term contracts exceed the District's load in August, the opposite is true
during Winter. Thus Figure 12 indicates that during the winter months, wind, battery storage29,
natural gas-fired generation, and spot market purchases play a key role in serving the evening
29 Battery storage typically charges during the early and late morning hours and discharges during the late evening
hours when the net load (load net of solar generation) is the highest during the day.
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ramps. In contrast, in August, very little natural gas-fired generation is needed to serve the
District loads, and the District will be mostly making spot market and REC sales.
Figure 12: Seasonal Supply Stack with Contracted Resources:
December vs. August 2040 (Wet Year)
50,000 2040 December Hourly Profile(kWh)
40,000
30,000
`3 zoaoa '
10,000 I I r
1 1
MAW)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 I6 17 18 19 20 21 22 23 24
HE
Geothermal Landfill Gas W.steHeat Hydro
Wind Solar MStorage MNatural Gas
®New 5-Year Market Purchase MSpot Market Purchase —Load
50,000 2040 August Hourly Profile(kWh)
4g000
30,000
`3 20,000
10,00o I I I
(1o,aao)
1 2 3 4 5 6 ] 8 9 10 31 12 13 14 15 16 1] 38 19 20 21 22 23 24
HE
Geothermal Landfill Gas Waste Heat Hydro
Wind Solar Storage MNatural Gas
®New 5-Year Market Purchase m5pot Market Purchase —Load
The Recommended portfolio allows the District to keep the average procurement costs at
reasonable levels, which range from 8.5 C/kWh to 9.9 C/kWh over the planning period, as
shown in Figure 13 below. The Net Present Value (NPV) of the total cost of procurement over
17 years (2024-2040) at a 5% discount factor for the Recommended portfolio is calculated at
$201.5 million.
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Figure 13: District Annual Average Procurement Costs ($/kWh): 2024-2040
$0.120
$0.099 $0.098 $0.098 0 099
2
$0.100 $0.094 $0.089 $0.092 $0.091 $0.092 $0.096 $0.094 $0.094 $0.097 $0.096 $0.098
3 $0.08 $0.085
$0.080
ij $0.060
m
T
> $0.040
Q
$0.020
Median Dry Median Wet Wet Median Wet Wet Dry Median Dry Dry Wet Dry Median Median Wet
2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040
Year
Consistent with the IRP methodology Step 4, we developed four (4) additional portfolios. The
description of these portfolios, as well as the overall cost of procurement over the planning
period, are summarized in Table 8.
Table 8: Scope and Cost (M$) Performance of Recommended Portfolio Relative to Alternative
Portfolios
Portfolio Name Portfolio Description NPV(M$)
Recommended Balanced Portfolio $201.5
No New PPA (NNP) No new contracted resources, and rely solely $229 0
on market purchases for incremental needs
No CVP, No Stampede, Add 4MW each of new
No CVP, No Stampede utility-scale solar&4-hour storage, 1MW of $210.8
TDPUD storage and 2MW of community solar
No battery storage (4-hr or 8-hr) and 4.5MW
No Storage, High Geothermal $192.6
more geothermal resource
Increase community solar by 10 MW, Internal
High Internal Gen 4-hour battery storage by 3MW, Utility-scale 4- $217.6
hour battery storage by 2.5MW, and reduce
geothermal by 3MW.
The recommended portfolio is slightly less cost-effective than the portfolio with no storage and
high geothermal. However, TDPUD's ability to contract with high levels of geothermal is
uncertain, and losing the storage paired with solar increases congestion exposure. The No New
PPA (NNP) portfolio that includes no new resources is the least cost-effective at $229 million
NPV. This portfolio also fails to meet the PRIM, RPS, and GHG-free goals, as shown in Table 9,
compared to the Recommended portfolio that mostly meets these criteria (Table 7). The NNP
portfolio requires the District to purchase RA and RECs from the market during all years to meet
these criteria.
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Table 9: Performance of NNP Portfolio in Meeting Reliability and State Policy Criteria: CY
2025, 2030, 2035 and 2040
Criteria 2025 2030 2035 2040
Contracted PRM (%) 85%* 76%* 67%* 61%*
Contracted RPS(%) 51% 49%** 41%** 40%**
GHG Free (%) 55% 54% 42%** 42%**
* Requires additional RA capacity purchase to meet 115% PRM
** Requires additional REC purchase to meet RPS goals of 60%
beyond 2030.The GHG-free goals of 90% by 2035 and 95% by 2040
are not met by the NNP portfolio.
Analysis of the results for the five portfolios, indicates that geothermal generation is key in
managing costs while meeting the RA and GHG goals.30 We consider geothermal as the proxy
for other potential baseload resources, such as biomass and landfill gas. In the future, the
District may be able to consider other clean firm resources, such as green hydrogen 31 and SMR,
in its portfolio should they become feasible and economical.
Sensitivity Analysis
As described earlier, in the TDPUD IRP model we have the capability to model multiple
scenarios. For the Base scenario, we have made certain assumptions about load levels, hydro
conditions, gas/energy prices, availability of PPA resources at certain prices, etc. For the Base
scenario, we have developed a recommended portfolio with a certain combination of PPA
resources and evaluated its performance given the Base Scenario assumptions. We also
evaluated the performance of additional resource portfolios (such as NNP, No CVP/Stampede,
etc.) with different combinations of PPA resources and market purchases given the Base
scenario assumptions.
We also developed a range of sensitivity values for key variables, such as Hydro conditions,
Loads, Natural Gas/Energy Market prices, PPA price, 5-year Market Purchase price, Resource
Adequacy Counting, etc. that could affect the performance of the alternative portfolios
consistent with the IRP methodology step 5. In Table 10, we summarize the changes to the key
variables used in the sensitivity analysis. For example, the geothermal PPA price is assumed to
be 25% higher in the High scenario relative to the Base scenario, whereas the Solar PPA prices
are assumed to be 8% lower and 15% higher relative to the Base scenario in the Low and High
scenarios, respectively. Early Hydro sensitivity changes the hydro condition pattern compared
to the Base scenario (see Table 4). The Low Early Hydro scenario assumes all three early years
to be wet, driving the overall cost of procurement down. In contrast, the High Early Hydro
scenario assumes all three early years to be dry, which drives up the overall cost of
procurement relative to the Base scenario.
10 The performance for the remaining three portfolios are provided in Appendix B.
11 See https://www.universitvofcalifornia.edu/news/renewable-clean-hydrogen-power-coming-california-heres-
what-you-need-know
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Table 10: Key Parameters Considered Under Sensitivity Analysis
Sensitivity Parameter Low(%) I a ' ' '
Below Base
W-AMM771:
NVE Transmission Charge ($/MWh) Base 50% Currently at$6/MWh vs.
CAISO $15/MWh
PPA Price 6%-15% 15%-25% Depending on the
resource
Natural Gas/Energy Market Price 15% 25%
RA Base CPUC CPUC counting rules
provide lower RA credit
Load -8.5% -9.1%
Early Hydro Wet Dry
New 5-Year Market Purchase Price 20% 20%
LV TAC on CVP Deliveries Base LV TAC Base scenario assumes
applies CVP deliveries exempt
from LV TAC
We stress-tested the performance of the Recommended portfolio using the extreme ranges of
each sensitivity parameter, changing one variable at a time, as shown in a tornado diagram in
Figure 14. Various combinations of these sensitivities can be developed to create additional
scenarios to further test the robustness of the alternative portfolios, though for simplicity, the
IRP study has concentrated on evaluating Portfolio performance with single sensitivity
parameter changes.
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Figure 14: Recommended Portfolio Performance Under Uncertainty
wVE Transmission Charge
prxpn"°
waanergm Market Price
RA $209
Loan
cn
w Early Hydro
New 5-Y°",Market Purchase Price
Lvr«o""ovpDeliveries
u180 $190 ueoo $e10 $uuo $uoo
NPV o,Cost(M$)
As shown in Figure 14, the Recommended portfolio costs are most sensitive tochanges in the
load assumptions. Under the high load forecast, the portfolio cost increased by approximately
$12 million to a total of$2l3 million NPV. This portfolio is also sensitive to the PPA price,
especially onthe higher side, given the large portion of PPA contracted resources in this
portfolio. NVE transmission charges have some impact on costs, but only local resources
(cornnnunityso|arandTDPUD4'hourstorage) canavoidthesecharges, and |irnitationsonthe
amount of such resources make this a less important decision factor. The NG/Energy Market
price, and RA uncertainties have only moderate cost impacts as this portfolio hedges those risks
via significant long-term contracting. All other uncertainties are insignificant. Overall, the
Recommended portfolio performs very well under uncertainty.
On the other hand, the NNP portfolio performs very poorly, and has a higher exposure to
uncertainty, as shown in Figure 15.32 The expected cost of NNP of$229.O million NPV is
significantly higher than the Recommended Portfolio. It is even costlier at $257 million, if the
loads are higher than anticipated. The NG/Energy Marker Price volatility is extremely high for
zzThetomadodiagramsfortheremainingthreeportfo|iosareprovidedinAppendix8.
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the NNP portfolio due to high reliance on the market price purchases. The PPA price has no
impact nn cost uncertainty asno new resources are being procured.
Figure15: NNP Portfolio Performance Under Uncertainty
wvs Transmission Charge
ppApri=
we/s=rgv Market Price
nx
cc
a.
Load
21
23
� Early Hydro
New n-Y°u,Market Purchase Price
$230
uvrAo=ovpDeliveries
$210 $uuo $uxn $240 $uon *cso
NPVof Cost(M$)
Conclusion
Overall, the Recommended portfolio meets all projected dernandandisre|iab|einternnsof
maintaining planning reserve margin. |t has one of the lowest overall cost of procurement, and
reduces exposure to market volatility. |t complies with the State's environmental goals and
policies. It includes required resource diversity and is a good fit in terms of balancing resources
against loads. We have also tested that the Recommended portfolio performs well under a
range ofsensitivities. We recommend that the District explore the potential for increasing the
proportion of geothermal or other base|nad resources into the Recommended portfolio, with a
corresponding decrease in reliance on solar plus storage, since this potentially could result in
lower overall costs, while also increasing resource diversity
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Appendix A: District's Compliance with Key State Policy Legislation and Goals
District's Compliance with Renewable Portfolio Standard (RPS)
On October 2, 2013, the District Board approved the Renewable Energy Resources Procurement
Plan per the requirements of Senate Bill (SB) X1-2 (2011). This plan defined the minimum
required percentage (RPS) of renewable energy resources compared to retail sales per three-
year compliance period to the end of 2020. Other legislation has increased the RPS
requirements and extended the compliance periods to the end of 2030. In 2015, SB 350 was
signed into law, which mandated a 50% RPS by December 31, 2030. In 2018, SB 100 was signed
into law, which increased the RPS to 60% by 2030 and requires all state's electricity to come
from carbon-free or clean resources by 2045. In addition, lawmakers passed SB 1020 in 2022,
which requires 90% clean electricity by the end of 2035 and 95% by the end of 2040 as
intermediate milestones to the target of 100% clean energy by 2045. Compliance periods and
RPS requirements are as follows:
• Period 1 -January 1, 2011 through December 31, 2013 - 20% RPS;
• Period 2 -January 1, 2014 through December 31, 2016 - 25% RPS;
• Period 3 -January 1, 2017 through December 31, 2020 - 33% RPS;
• Period 4 -January 1, 2021 through December 31, 2024 -44% RPS;
• Period 5 -January 1, 2025 through December 31, 2027 - 50% RPS; and
• Period 6 -January 1, 2028 through December 31, 2030 - 60% RPS.
The District's final RPS amount is the ratio of all qualifying renewable energy received divided
by the District's total retail energy sales, as defined by the California Energy Commission (CEC).
Section 3201(bb) of CEC regulations define retail energy sales as: "Sale of electricity by a
publicly owned utility (POU) to end-use-customers and their tenants, measured in MWh". This
does not include energy consumption by a POU, electricity used by a POU for water pumping,
or electricity produced for onsite consumption (self-generation)."
Table A-1 summarizes the year-by-year RPS and GHG-free goals for the planning period.
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Table A-1: State RPS (%) and GHG-free (%) Goals: 2024-2040
GHG-Free
Year RPS
2024 44% N/A
2025 47% N/A
2026 49% N/A
2027 50% N/A
2028 55% N/A
2029 57% N/A
2030 60% N/A
2031 60% 78%
2032 60% 81%
2033 60% 84%
2034 60% 87%
2035 60% 90%
2036 60% 91%
2037 60% 92%
2038 60% 93%
2039 60% 94%
2040 60% 95%
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AppendixR• Model Assumptions
Table B-1: Performance of No CVP, No Stampede Portfolio in Meeting Reliability and State
Policy Criteria: CY 2025, 2030, 2035 and 2040
Criteria 2025 2030 2035 2040
Contracted PRM (%) 81%* 118% 129% 117%
Contracted RPS(%) 53% 102% 113% 106%
GHG Free (%) 55% 106% 113% 106%
* Requires additional short-term RA capacity purchases to meet 115%
PRM.The RPS target increases from 45%in 2025 to 60%in 2030.The GHG
Free target is 90%in 2035 and 95%in 2040.
Figure B-1: No CVP, No Stampede Portfolio Performance Under Uncertainty
i I !
NVE Transmission Charge 1 $216
I I I I I
I I I I
I I I I I
I I I
I I I I
PPA Price $203 $2;7
i I i i
$207 $216
I
I i i
NG/Energy Market Price
I i i
I I I
I i i i
I I I I
I i i i i
N
d RA $�17
d I
M
a
w Load $199 $222
i I
in $211
� I
Early Hydro $209
I I I
I I I
I I I
$211
New 5-Year Market Purchase Price $209
I
I i i i
$210
LV TAC on CVP Deliveries
I i i i
$210
$190 $200 $210 $220 $230 $240
NPV of Cost(M$)
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Table B-2: Performance of No Storage, High Geothermal Portfolio in Meeting Reliability and
State Policy Criteria: CY 2025, 2030, 2035 and 2040
Criteria 2025 2030 2035 2040
Contracted PRM (%) 96%* 116% 127% 116%
Contracted RPS(%) 55% 114% 122% 116%
GHG Free (%) 59% 121% 124% 118%
* Requires additional short-term RA capacity purchases to meet 115%
PRM.The RPS target increases from 45%in 2025 to 60%in 2030.The GHG
Free target is 90%in 2035 and 95%in 2040.
B-2: No Storage, High Geothermal Portfolio Performance Under Uncertainty
NVE Transmission Charge $197' ' I
I I I
I
PPA Price 1 $188 $2 6
$190 $195
NG/Energy Market Price
I I I I
N
d RA ( $200
E
li
_ $203
Load $182
T
H $192
c
y I
N Early Hydro i
$191
' I
I
$19
New 5-Year Market Purchase Price 1 $191
I I I
$193
LV TAC on CVP Deliveries
$1912
$170 $180 $190 $200 $210 $220 $230
NPV of Cost(M$)
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Table B-3: Performance of High Internal Gen Portfolio in Meeting Reliability and State Policy
Criteria: CY 2025, 2030, 2035 and 2040
Criteria 2025 2030 2035 2040
Contracted PRM (%) 96%* 127% 127% 115%
Contracted RPS(%) 55% 99% 98% 94%
GHG Free (%) 59% 106% 100% 97%
* Requires additional short-term RA capacity purchases to meet 115%
PRM.The RPS target increases from 45%in 2025 to 60%in 2030.The GHG
Free target is 90%in 2035 and 95%in 2040.
Figure B-3: High Internal Gen Portfolio Performance Under Uncertainty
I
NVE Transmission Charge $223 ii
i i I I
PPA Price 1 i $211 $232
i
$214
,
jI iiiiiiiiiiiiIIIi ijjIi
I
24
NG/Energy Market Price
RA
$225
L
$
229
Load $206
ta 1$218
A Early Hydro $216 2
$218
New 5-Year Market Purchase Price $217 $218
LV TAC on CVP Deliveries
iiIiiiIIIIIIII
$190 $200 $210 $220 $230 $240 $250
NPV of Cost(M$)
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Appendix C: Additional . . . Forecast Methodology
PEV and Bass Diffusion Modeling
PEV vehicle stock is forecast using a bass diffusion model (sometimes known as a learning curve)
for new technologies which estimates the EV market saturation year over year by optimizing the
coefficients for innovators (p) and imitators (q) to effectively reach market share targets.33 The
innovator coefficient represents early adopters, and the imitator coefficient represents those
who adopt due to observing the innovator adoptions. These coefficients are determine using the
current trend in vehicle stock and the expected market share.34 Aspen optimized the coefficients
to minimize the sum of the squared error term given the current trend in PEV ownership vs. the
predicted values for the historical period from 2018-2023. Figure C-1 demonstrates the expected
market share for residential PEVs from the model in the mid load case, with sales peaking in
2030.35
Figure C-1: Bass Diffusion Curve for Market Adoption of Residential PEVs
3000
2500
N 2000
a�
t
a 1500
0
1000
500
0
M 01 6 ri N M �t un [D n 0o a1 O ri N rn , Ln [D n cc a1 O
rl rl N N N N N N N N N N m m m m co M M M M M *
O O O O O O O O O O O O O O O O O O O O O O O
N N N N N N N N N N N N N N N N N N N N N N N
PEV Market Share
The PEV stock is multiplied by NREL's hourly charging profile to calculate the total load
requirement for residential charging.31
33 The Tahoe-Truckee Readiness Plan provides market share estimates for a low, medium and high case which
translates to the District low, medium and high load forecast scenarios.
34 The current and historical plug-in electric vehicle data is sourced via DMV data for the relevant Truckee zip
codes. This gives a count and trend line basis for estimating vehicle ownership by fuel type in the forecast period.
CA DMV Vehicles by fuel type and zip code: https://data.ca.gov/dataset/vehicle-fuel-type-count-bv-zip-code
35
36 The LDV EV load profile is estimated using the EVI-Pro Lite tool which provides charging profiles for residential LDV
PEVs for 1000 cars on a 15-minute basis. The load profile was aggregated to hourly kWh/vehicle. The EVI-Pro Lite
tool was developed under a collaborative effort by NREL, CEC, DOE funding and LBNL: https://afdc.energy.gov/evi-
rp o-lite
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Energy Efficiency and Electrification Costs
Generally, EE costs are estimated using reported $/kWh estimates for TDPUD programs in the
past. The cost factor escalates over time with diminishing returns for each dollar spent on EE as
savings become more costly in future years. The $/kWh cost also includes the present value of
future savings from program dollars spent in each year. In the low load case, EE cost is assumed
to be cheaper as new programs capture EE potential savings benefits and EE paired with
electrification. Electrification spending is sourced from Truckee's 2022 program results on an
average $/kWh added basis. These costs could decline as technology improves for electric space
heating and Truckee's building electrification programs mature. Figure C-2 displays spending
results for each of the load forecast scenarios as well as the additional Efficient Electrification
scenario.
Figure C-2: Energy Efficiency and Electrification Spending by Load Forecast Scenario
53,000,000 $3,000,000
52,SOO,000 S2 sao.0D0
52,000,000 ;,, S21000,0DO
$2,500,000 51,500,000
O q
S1,ODD,000
S1,000,000 'e
C4 JJJJ IJJJ �I
5500,000 y 5500,000
Y 50 SO
2025 2030 2035 2040 2025 2030 2035 2040
�Low Load Case EE s Mid Load Case EE
�Low Load Case Electrification �Mid Load Case Electrification
—NET Low Load Case —NETMid Load Case
5,3,000,ODO $3,000,000
S2,SCO,ODO $2,500,000
$2.000,000 ;,F $2,000,000
o 51,500,ODv 3 s1,soD,00D
4 A
S1,000,0DO a $1,000,D00
C {
{ Q
T SSW OW 5500,000
73
SO s0
I il 1
2025 2030 2035 2040 2025 2030 2035 2040
�High Lwd Case EE �Effident EWctrificaton Case EE
�High Load Case Electrification �Efficient EkcWifintion Case Electrification
-NET Mich Load Case -Net Efficient Electrification
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Appendix D: Exploratory Load Scenarios
This appendix contains three additional load scenarios, capturing the impacts of i) Heavy duty
truck charging; ii) 100% residential PEV charging; and iii) Efficient Electrification. Table D-1
provides summary results for each exploratory scenario; the table repeats the Mid case load
forecast for ease of comparison. Assumptions not specified are the same as in the Mid case.
Table D-1: Exploratory Load Forecast Scenario Descriptions
Scenario Annual Load in 2040 Peak Load in 2040 Description
•Historical EEtrend
•Mid case solar
Mid Case 247 GWh 47.5 MW •Mid case for residential and public EV charging
•Baseline Annual Trend(2.1%)
•Mid case for electrification
HD Truck Charging 291 GWh 52.5 MW •Increase of 43.8 GWh annually by 2040
•Increase of 5 MW peak load requirement
•Market share of 18,000 residential PEVs
100%Residential PEV Charging 270 GWh 53 MW -100%residential PEV adoption
•Increase of 23 GWH annually by 2040
•Increase of 5.5 MW peak load requirement
•Low load case potential EE savings
Efficient Electrification 228 GWh 44 MW •Accelerated electrification
•Decrease of 19 GWh annually by 2040
•Decrease of 3.5 MW peak load requirement
Additional Details of HD Truck Charging
Aspen looked at potential volume of trucks moving through the Truckee corridor however, the
volume of truck traffic likely exceeds the capacity and space requirement needed to charge all of
the trucks passing through.37 Charging one of these tractor-trailers takes 1-2 hours and uses
approximately 1 MW each hour.38 This scenario assumes 4-6 MW worth of chargers operating
concurrently which accommodates 100 to 150 trucks per day. Locating space for these trucks to
stop and charge and the overall infrastructure cost for Truckee requires further study. Other
concerns include decreased efficiency of batteries in cold weather and the accelerated
deterioration of highway roads due to the increased average truck weight due to the heavy
batteries on board.39
37 Aspen sourced truck traffic data from Cal Trans which gives the Annual Average Daily Truck Traffic by highway.
See : https://dot.ca.gov/programs/traffic-operations/census.
38 This is assuming the largest truck under development with the largest charging capability in order to serve all
trucks through the Truckee corridor.See article for example charging specs: https://www.ptolemus.com/insight/is-
tesla-semi-a-game-changer-part-l-tesla-semi-versus-other-electric-trucks/
39 The California Transportation Commission released a study detailing potential truck charging costs for station
developments, road maintenance and statewide estimates for zero-emissions freight stations needed. See:
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Appenclix E: Acronym List
AMI Advanced Metering Infrastructure
BAA Balancing Authority Area
BTM Behind-the-Meter
CAISO California ISO
CEC California Energy Commission
CFPP Carbon Free Power Project
CMUA California Municipal Utilities Association
CVP Central Valley Project
EE Energy Efficiency
FY Fiscal Year
GHG Greenhouse Gas
IRP Integrated Resource Plan
LSE Load Serving Entity
LV Low-Voltage
NNP No New PPA
NPV Net Present Value
NTUA Navajo Tribal Utility Authority
NVE NV Energy
GATT Open Access Transmission Tariff
PEV Plug-in Electric Vehicle
POU Publicly Owned Utility
PPA Power Purchase Agreement
PRM Planning Reserve Margin
RA Resource Adequacy
REC Renewable Energy Credit
RPS Renewable Portfolio Standard
SB Senate Bill
SC Scheduling Coordinator
SMR Small Modular Reactor
SPPC Sierra Pacific Power Company
TAC Transmission Access Charge
TDPUD Truckee Donner Public Utility District
TCID Truckee-Carson Irrigation District
UAMPS Utah Association of Municipal Power Systems
WAC Wheeling Access Charge
WAPA Western Area Power Administration
https://catc.ca.gov/-/media/ctc-med is/docu ments/ctc-workshops/2023/063023-draft-sb671-assessment-
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